Search Results for author:
Found 6 papers, 4 papers with code
Permutation Invariant Recurrent Neural Networks for Sound Source Tracking Applications
Conventional recurrent neural networks (RNNs), such as the long short-term memories (LSTMs) or the gated recurrent units (GRUs), take a vector as their input and use another vector to store their state.
Position tracking of a varying number of sound sources with sliding permutation invariant training
Recent data- and learning-based sound source localization (SSL) methods have shown strong performance in challenging acoustic scenarios.
Direction of Arrival Estimation of Sound Sources Using Icosahedral CNNs
In this paper, we present a new model for Direction of Arrival (DOA) estimation of sound sources based on an Icosahedral Convolutional Neural Network (CNN) applied over SRP-PHAT power maps computed from the signals received by a microphone array.
Music Boundary Detection using Convolutional Neural Networks: A comparative analysis of combined input features
The objective of this work is to establish a general method of pre-processing these inputs by comparing the inputs calculated from different pooling strategies, distance metrics and audio characteristics, also taking into account the computing time to obtain them.
Robust Sound Source Tracking Using SRP-PHAT and 3D Convolutional Neural Networks
In this paper, we present a new single sound source DOA estimation and tracking system based on the well-known SRP-PHAT algorithm and a three-dimensional Convolutional Neural Network.
gpuRIR: A python library for Room Impulse Response simulation with GPU acceleration
The Image Source Method (ISM) is one of the most employed techniques to calculate acoustic Room Impulse Responses (RIRs), however, its computational complexity grows fast with the reverberation time of the room and its computation time can be prohibitive for some applications where a huge number of RIRs are needed.
